Padraic Byrne
@padraicbyrne
I build scalable data linkage pipelines and statistical analysis solutions.
What I'm looking for
I'm currently working with the Central Statistics Office Data Engineering team, improving large-scale data linkage workflows through dataset cleaning, joining, validation, and ETL pipeline development.
I've helped migrate R-based workflows to Apache Spark for distributed processing on Hadoop, and previously worked with Eli Lilly's statistical team on manufacturing-process reports, product limits, process capability metrics, peer reviews, and presentations for non-technical stakeholders.
My first-class honours degree in Data Science and Analytics is grounded in statistical modelling, machine learning, and data analysis. My final-year project compared clustering algorithms with a focus on spectral clustering, while my Eli Lilly project evaluated statistical approximations for real-time process monitoring.
Experience
Work history, roles, and key accomplishments
Graduate (Data Engineering)
Central Statistics Office
Sep 2025 - Present (11 months)
Evaluating data engineering methods to improve data linkage quality and performance. Collaborating with the data engineering team on cleaning, joining, and validating administrative datasets, and creating ETL pipelines.
Worked with the statistical team to produce technical reports for manufacturing processes. Calculated and implemented various product limits and process capabilities (Cp, Cpk), and performed statistical peer reviews.
Education
Degrees, certifications, and relevant coursework
University College Cork
Bachelor of Science, Data Science and Analytics
2021 - 2025
Grade: First Class Honours (1.1)
BSc Data Science and Analytics with First Class Honours. Coursework included machine learning, multivariate data analysis, time series, and Bayesian statistics.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Portfolio
github.com/ByrnePadraicJob categories
Skills
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